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from __future__ import annotations
import base64
import json
from aiohttp import ClientSession, BaseConnector
from ...typing import AsyncResult, Messages, ImageType
from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
from ...image import to_bytes, is_accepted_format
from ...errors import MissingAuthError
from ..helper import get_connector
class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin):
label = "Gemini API"
url = "https://ai.google.dev"
working = True
supports_message_history = True
needs_auth = True
default_model = "gemini-1.5-pro"
default_vision_model = default_model
models = [default_model, "gemini-pro", "gemini-1.5-flash", "gemini-1.5-flash-8b"]
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
stream: bool = False,
proxy: str = None,
api_key: str = None,
api_base: str = "https://generativelanguage.googleapis.com/v1beta",
use_auth_header: bool = False,
image: ImageType = None,
connector: BaseConnector = None,
**kwargs
) -> AsyncResult:
model = cls.get_model(model)
if not api_key:
raise MissingAuthError('Add a "api_key"')
headers = params = None
if use_auth_header:
headers = {"Authorization": f"Bearer {api_key}"}
else:
params = {"key": api_key}
method = "streamGenerateContent" if stream else "generateContent"
url = f"{api_base.rstrip('/')}/models/{model}:{method}"
async with ClientSession(headers=headers, connector=get_connector(connector, proxy)) as session:
contents = [
{
"role": "model" if message["role"] == "assistant" else "user",
"parts": [{"text": message["content"]}]
}
for message in messages
if message["role"] != "system"
]
if image is not None:
image = to_bytes(image)
contents[-1]["parts"].append({
"inline_data": {
"mime_type": is_accepted_format(image),
"data": base64.b64encode(image).decode()
}
})
data = {
"contents": contents,
"generationConfig": {
"stopSequences": kwargs.get("stop"),
"temperature": kwargs.get("temperature"),
"maxOutputTokens": kwargs.get("max_tokens"),
"topP": kwargs.get("top_p"),
"topK": kwargs.get("top_k"),
}
}
system_prompt = "\n".join(
message["content"]
for message in messages
if message["role"] == "system"
)
if system_prompt:
data["system_instruction"] = {"parts": {"text": system_prompt}}
async with session.post(url, params=params, json=data) as response:
if not response.ok:
data = await response.json()
data = data[0] if isinstance(data, list) else data
raise RuntimeError(f"Response {response.status}: {data['error']['message']}")
if stream:
lines = []
async for chunk in response.content:
if chunk == b"[{\n":
lines = [b"{\n"]
elif chunk == b",\r\n" or chunk == b"]":
try:
data = b"".join(lines)
data = json.loads(data)
yield data["candidates"][0]["content"]["parts"][0]["text"]
except:
data = data.decode(errors="ignore") if isinstance(data, bytes) else data
raise RuntimeError(f"Read chunk failed: {data}")
lines = []
else:
lines.append(chunk)
else:
data = await response.json()
candidate = data["candidates"][0]
if candidate["finishReason"] == "STOP":
yield candidate["content"]["parts"][0]["text"]
else:
yield candidate["finishReason"] + ' ' + candidate["safetyRatings"]
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